An Improved DR Algorithm Based on Target Extrapolating in ROIA Cloud Platform
Author(s) -
Dong Liu
Publication year - 2013
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2013/637328
Subject(s) - computer science , cloud computing , scalability , distributed computing , algorithm , resource (disambiguation) , server , architecture , mode (computer interface) , database , human–computer interaction , operating system , computer network , art , visual arts
Real-time Online Interactive Application (ROIA) is an emerging distributed application recently. ROIA needs a highly robust and efficient architecture to cope with the huge concurrent users. Previous works are almost based on the C/S or P2P mode, and their scalability and resource utilization are relatively low. So we try to take advantage of the cloud computing technologies to achieve higher scalability and resource utilization. However, as ROIA servers focused on several data centers in cloud computing rather than being scattered in many areas, it will increase in part users' network delays and affect their user experiences in ROIA. To cope with this problem, we propose an improved Dead Reckoning (DR) algorithm. Traditional DR algorithm is mostly based on the classic formula of physics to predict, without taking the influence of the user's target under the different situations into account, so there are some limitations. This paper proposes an improved DR algorithm based on target-extrapolating in a cloud platform for ROIA, elaborates the basic idea of the improved algorithm and the computational model formula, and then carries out a simulation experiment. The analyses of the simulation results show that the improved algorithm is superior to traditional one. © 2013 Dong Liu.
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